Predictive pre‐activation of orthographic and lexical‐semantic representations facilitates visual word recognition

Abstract

To a crucial extent, the efficiency of reading results from the fact that visual word recognition is faster in predictive contexts. Predictive coding models suggest that this facilitation results from pre‐activation of predictable stimulus features across multiple representational levels before stimulus onset. Still, it is not sufficiently understood which aspects of the rich set of linguistic representations that are activated during reading—visual, orthographic, phonological, and/or lexical‐semantic—contribute to context‐dependent facilitation. To investigate in detail which linguistic representations are pre‐activated in a predictive context and how they affect subsequent stimulus processing, we combined a well‐controlled repetition priming paradigm, including words and pseudowords (i.e., pronounceable nonwords), with behavioral and magnetoencephalography measurements. For statistical analysis, we used linear mixed modeling, which we found had a higher statistical power compared to conventional multivariate pattern decoding analysis. Behavioral data from 49 participants indicate that word predictability (i.e., context present vs. absent) facilitated orthographic and lexical‐semantic, but not visual or phonological processes. Magnetoencephalography data from 38 participants show sustained activation of orthographic and lexical‐semantic representations in the interval before processing the predicted stimulus, suggesting selective pre‐activation at multiple levels of linguistic representation as proposed by predictive coding. However, we found more robust lexical‐semantic representations when processing predictable in contrast to unpredictable letter strings, and pre‐activation effects mainly resembled brain responses elicited when processing the expected letter string. This finding suggests that pre‐activation did not result in “explaining away” predictable stimulus features, but rather in a “sharpening” of brain responses involved in word processing.

Individual word representations dissociate from linguistic context along a cortical unimodal to heteromodal gradient

“…The direction of each investigated parameter's effect on the evoked response across the surface parcels changed over time; yet, for most parameters, the relation to the gradient (i.e., whether a parameter's absolute effect was strongest at the sensory or heteromodal end of the gradient) did not change. The fact that most parameters were associated with the gradient in both early and later time windows, and the absence of explicit evidence for temporal changes for most parameters, is compatible with an interactive account of parallel processing across multiple linguistic levels (e.g., Clarke et al, 2011;2013;Cornelissen et al, 2009;Eisenhauer et al, 2022;Kaestner et al, 2021;Mollo et al, 2017;Teige et al, 2019). This interactive processing is also reflected along the principal gradient: both ends of the gradient are activated in similar time windows but represent different aspects of linguistic information.…”

“…Word frequency and semantic similarity did not significantly affect self-paced reading response times in the present study, potentially as self-paced reading responses were fast (mean: 380 ms) and more sensitive to measures reflecting earlier stages of word recognition. Nevertheless, previous studies quite consistently provided evidence for faster reading of high vs. low frequency words (e.g., Dufau et al, 2015;Eisenhauer et al, 2022;Juhasz and Rayner, 2007) as well as high vs. low semantic similarity (e.g., Hofmann et al, 2022;Pynte et al, 2008a;2008b;Salicchi and Lenci, 2021;Wang et al, 2010).…”

“…The copyright holder for this preprint this version posted April 25, 2023. ; https://doi.org/10.1101/2023.04.25.538257 doi: bioRxiv preprint Faisca et al, 2019;Hauk and Pulvermueller, 2004;Simon et al, 2012). Word length and OLD20 effects can also show different effect directions depending on the time window (Assadollahi and Pulvermueller, 2004;Eisenhauer et al, 2022;Hauk and Pulvermueller, 2004).…”

Access to meaning from visual input: Object and word frequency effects in categorization behavior.

“…This explanation also relates to theories more deeply concerned with the neuronal preparation for highly predicted incoming stimuli, like predictive coding theories (Rao & Ballard, 1999) or sharpening (Kok et al, 2012, 2017). Evidence from similar experiments using words (Eisenhauer et al, 2019, 2021; Gagl et al, 2020), objects (Richter et al, 2018; Summerfield et al, 2008), faces (Olkkonen et al, 2017), or cross-modal priming paradigms (Kok et al, 2012, 2017) have provided findings that indicate feature-based prediction effects.…”

“…Besides, we wanted to test the role of semantic processing on the WF and OF effects more explicitly. The critical manipulation, therefore, contrasted cross-modal and uni-modal priming (Eisenhauer et al, 2019, 2021; Scarborough et al, 1977; Tversky, 1969). As described earlier, only cross-modal priming involves conceptual/semantic information transfer from prime to target processing without shared perceptual processing.…”